Diagnostic plots for pathClassifier.
plotClassifierROC(mix)The result from pathClassifier.
Diagnostic plots of the result from pathClassifier.
itemTopROC curves for the posterior probabilities (mix\$posterior.probs)
and for each HME3M component (mix\$h). This gives information about what response
label each relates to. A ROC curve with an AUC < 0.5 relates to y = 0.
Conversely ROC curves with AUC > 0.5 relate to y = 1.
itemBottomThe likelihood convergence history for the HME3M model. If the parameters
alpha or lambda are set too large then the likelihood may decrease.
Other Path clustering & classification methods:
pathClassifier(),
pathCluster(),
pathsToBinary(),
plotClusterMatrix(),
plotPathClassifier(),
plotPathCluster(),
predictPathClassifier(),
predictPathCluster()
Other Plotting methods:
colorVertexByAttr(),
layoutVertexByAttr(),
plotAllNetworks(),
plotClusterMatrix(),
plotCytoscapeGML(),
plotNetwork(),
plotPathClassifier(),
plotPaths()